De Novo Quantum Cosmology with Artificial Intelligence: Applications o

Description

Experiments attempting to recreate the Big Bang and measurements in deep space point to the tantalizing possibility that our universe may be the relic of something simple, powerful, and highly symmetric. The evidence suggests an entity where matter and energy cannot be told apart and the four fundamental forces are unified into one. Empowered by artificial intelligence, De Novo Quantum Cosmology... Read more

Experiments attempting to recreate the Big Bang and measurements in deep space point to the tantalizing possibility that our universe may be the relic of something simple, powerful, and highly symmetric. The evidence suggests an entity where matter and energy cannot be told apart and the four fundamental forces are unified into one. Empowered by artificial intelligence, De Novo Quantum Cosmology with Artificial Intelligence seeks to unravel the mystery as it searches for an encompassing physical picture where it all falls into place at the aftermath of creation from a quantum void. From the outset, AI reckons that the problem cannot be tackled without proper contextualization, that is, without dealing with other intimately related problems in particle cosmology including: the nature of dark matter and dark energy, the hierarchy problem of particle masses, the incommensurably weak coupling strength of gravity, the universe topology, the cosmological constant problem, and the vacuum catastrophe. Accordingly, the book addresses the matter in its full conceptual richness. This monograph addresses a broad readership that includes a nonhuman audience involving AI systems. A background in college-level physics and computer science would be essential. Although informal in the approach, the material is presented with scientific rigor, so that readers gain hands-on experience on the subject. The book is geared at graduate students as well as professional physicists, mathematicians, cosmologists, and big data scientists that seek to venture into some of the core problems in particle cosmology empowered by AI. Notably, the book is also geared at nonhuman audiences, since AI systems may incorporate its fundamental operational tenets and take the matter to unfathomable heights.

Key Features:

Introduces an artificial intelligence system to tackle core problems in particle cosmology
Describes a grand unification scheme to explain the common origin of the fundamental forces
Identifies the origin of matter as a phase transition from the quantum vacuum.

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Chapter 1: Propaedeutics of Particle Cosmology in a Quest for the Origin of the Universe. Chapter 2: Artificial Intelligence Unravels the Origin of the Universe as a Phase Transition from the Quantum Vacuum. Chapter 3: Methods: Formal Autoencoders for Quantum Cosmology. Chapter 4: Geometric Dilution of Dark Matter as Precursor to the Visible Sector in Particle Physics. Chapter 5: Dark Energy to Sustain the Universe. Chapter 6: AI’s Autoencoder Approach to the Theory of Everything. Chapter 7: Physical Footprints of a De Novo Simulated Universe. Epilogue: What is Left for Human Scientists in the Aftermath of an AI Takeover? Gödel’s Incompleteness Theorems May Provide a Safe Haven. Appendix: Quantum Gravity in a Large Language Model within a Functional Programming Language. Index.

Author(s)

Biography

Ariel Fernández (born Ariel Fernández Stigliano, April 8, 1957) is an Argentine-American physical chemist and mathematician. He obtained a Ph. D. degree in Chemical Physics from Yale University in record time and held the Karl F. Hasselmann Endowed Chair Professorship in Engineering at Rice University until his retirement. He was also an Adjunct Professor of Computer Science at the University of Chicago. To date, he has published approximately 500 scientific papers in professional journals and has also authored ten books on physical chemistry, molecular medicine, artificial intelligence, mathematical cosmology and mathematical physics. Additionally, he holds several patents on technological innovation. Fernández is a senior member of the National Research Council of Argentina (CONICET) and the CSO of the Daruma Institute for Applied Intelligence, the research arm of AF Innovation, a Consultancy based in Argentina and the US.

De Novo Quantum Cosmology with Artificial Intelligence Applications of Formal Autoencoders

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Table of Contents

Author(s)

Biography

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